the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Aug 2023
The linkage between autumn Barents-Kara sea ice and European cold winter extremes
Abstract. Despite intense efforts to understand the links between the Arctic region and mid-latitudes, there is no consensus on the relationship between sea ice retreat and the frequency of occurrence of mid-latitude weather extremes (e.g., cold spells, heatwaves, droughts). By tracking monthly variabilities based on observational data, we show that a decline in sea ice over the Barents-Kara Seas in autumn is related to extreme cold winters over much of Europe. The winter temperature change in Europe is a direct response to a stationary Rossby wave generated by the lower troposphere diabatic heat anomaly as a result of sea ice loss over the Barents-Kara Seas in autumn, leading to a negative phase of North Atlantic Oscillation and more frequent episodes of the atmospheric blocking over Greenland and the North Atlantic. The negative phase of the North Atlantic Oscillation and enhanced blocking are closely related and mutually reinforcing, shaping the spatial distribution of cold anomalies over much of the European continent. Our results suggest a link between the unusual retreat in Barents-Kara Sea ice during autumn and the occurrence of intense European weather extremes in subsequent winter months. Nevertheless, climate models have difficulties to capture the variability and trend of the Artic sea ice and to capture the relationship between sea ice reduction and European winter extremes. Consequently, further work on this relationship on monthly time scales will improve our understanding of the prediction of midlatitude extreme events.
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RC1: 'Comment on egusphere-2023-1646', Anonymous Referee #1, 28 Aug 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1646/egusphere-2023-1646-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2023-1646', Anonymous Referee #2, 01 Sep 2023
This study examines the links between autumn sea ice in the Barents-Kara sea ice and European winter cold extremes. The authors find low sea ice is associated with a weakened stratospheric polar vortex, a negative NAO/AO, more frequent blocking, and more frequent cold extremes over Europe. The authors conclude from this that sea ice retreat is an important driver of winter weather extremes. The authors also perform an evaluation of the sea ice variability and sea ice-circulation links in climate models, and find they perform very poorly.
Overall, there are many fundamental issues with the analysis and interpretation. This includes assuming causation from correlation, sampling issues, and inappropriate model-observation comparisons. Even if some of these may be able to be addressed with major revisions (e.g. toning down conclusions and additional analysis), it is not clear to me what the novelty of the study is. Because of these reasons, I recommend this paper be rejected.
Note that while my comments are very similar to reviewer#1’s comments, I wrote this review before looking at their comments.
Major issues:
1. The authors assume the atmospheric circulation and temperature anomalies that are linked with reduced sea ice are caused by the reduced sea ice. There are strong statements about causality throughout the paper, even explicitly stating that the sea ice anomalies are causing the subsequent circulation anomalies. However, correlation does not necessarily imply causation. Indeed, there have been many studies arguing that these correlations are not caused by sea ice loss, but rather both are driven by the same circulation patterns. This is the case even when investigating the lagged connection from autumn sea ice to the winter circulation/temperatures, as is examined here (e.g. Peings 2019; Blackport and Screen 2021). Strong statements about the causality need to be removed and the issues with causality need to be discussed.
2. The analysis is based on very small sample sizes, and many of the results presented are not, or barely statistically significant. These weak and non-robust connections seen in the figures are often described in detail and with a lot of authority in the text as if are they very robust. In addition, it does not appear that the false discovery rate was controlled for in the maps (Wilks 2016), which would even further reduce the significance. Furthermore, it also has been shown that the relationship between autumn Barents-kara sea ice and the NAO is not robust and nonstationary over time, with it displaying opposite signed relationships in the recent past (Kolstad and Screen 2019). This further questions the robustness of the results presented here. For this paper to be publishable, the false discovery rate needs to be controlled for, and the authors would need to substantially revise the text to put less focus on links that are not statistically significant.
3. The model-observation comparisons are not appropriate and demonstrate a fundamental misunderstanding of the analysis and/or the data. The year-to-year variability in observations and in individual model runs is almost entirely due to internal variability. However, the phases of internal variability will not occur at the same time in each model realization (and in observations), so averaging over all model realizations will average out the internal variability. So of course the year-to-year variability in the model is low compared to observations, because you have removed the variability by averaging across the different runs! This flawed analysis leads the authors to make very strong statements about the capability of the models that are not supported.
To do the analysis correctly, you need to compare the observations to the spread of results in individual runs, not the ensemble mean. This is the case for both the analysis of the sea ice variability and the composites of the circulation over low and high sea ice. Note that you are probably going to want to use a lot more than 13 simulations for a proper comparison. The cross-ensemble spread will likely be very large due to internal variability, even within the same model (see e.g. Siew et al. 2021; Blackport and Screen 2021)
4. The novelty of the study is unclear. This study identifies the statistical connections between reduced sea ice in the Barents-Kara sea and the winter circulation and cold extremes. However, these links are all very well established and have been for a while now (e.g. Hopsch et al. 2012; Liu et al. 2012; Tang et al. 2013; Overland et al. 2015; Yang et al. 2016; Ruggieri et al. 2016; Blackport and Screen 2021) . There are still a lot of outstanding questions around this topic (e.g. the causality and the robustness of these connections), but this study does not address any of these. I don’t see any new insight that this study brings to the existing literature.
Other comments:
L13-15: I don’t really agree with this statement, at least for cold extremes, which this paper is about. It is well established that there are statistical correlations between the Arctic and midlatitude cold extremes. Where there is no consensus on is whether these statistical connections are a causal response to sea ice, whether they are relevant for climate change, plus many other questions.
L15-16: This statement is at best misleading about the results presented. I typically associate “decline in sea ice” with the long-term trend of disappearing sea ice, not year-to-year variability. This study uses detrended data, so it is not about the decline of sea ice. The long-term decline in sea ice is in fact associated with a reduction in cold extremes over Europe.
L21-22: Similar to above, the word “retreat” implies a long-term trend which is not what the paper is about.
L23:Artic --> Arctic
L40-42: I don’t follow the logic here. Why does the fact that there is a connection in observations suggest that the latter sea ice forces the atmosphere? The main message of Blackport et al. 2019 (that this sentence seems to be disputing) is that the correlation do not appear to be driven by sea ice.
L46-56: The evidence and theoretical basis for the mechanisms described here linking sea ice loss to the midlatitude circulation are heavily disputed (e.g. Barnes 2013; Hoskins and Woollings 2015; Barnes and Screen 2015; Blackport and Screen 2020; Siew et al. 2021). Overall, this introduction is not a very accurate representation of the literature, and it does not accurately capture the outstanding questions in field.
L61-64: It is an exaggeration to say that the capability of the models to simulate these things is ‘limited’. Models have their biases, but when like-for-like comparisons are made, models tend to do quite well (e.g Blackport and Screen 2021).
L80: Why these 13 models? There is a lot more model data than this that is publicly available. I would recommend using as much model data as possible because of the large amount of internal variability.
L112: I assume this should be below -0.8 standard deviations for the low years.
L112-115: Are the results sensitive to the exact threshold used? With so few years, they might be.
L132: I don’t see a wave-like pattern in the Z100 results.
L183-195: I am not seeing what the authors are seeing in Fig 4. It seems to me that the authors are overinterpreting small month-to-month changes that are not statistically significant (see major comment 2).
L204: I think that the ‘Z500’ should be ‘Z100’?
L348-350: Even ignoring the issues with the model-observation comparisons, how would this provide an explanation for the ‘suboptimal climate sensitivity assessments’? What suboptimal climate sensitivity assessments is this referring to?
References:
Barnes, E. A., 2013: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophys. Res. Lett., 40, 4734–4739, https://doi.org/10.1002/grl.50880.
Barnes, E. A., and J. A. Screen, 2015: The impact of Arctic warming on the midlatitude jet-stream: Can it? Has it? Will it? WIREs Clim. Change, 6, 277–286, https://doi.org/10.1002/wcc.337.
Blackport, R., and J. A. Screen, 2020: Weakened evidence for mid-latitude impacts of Arctic warming. Nature Climate Change, 10, 1065–1066, https://doi.org/10.1038/s41558-020-00954-y.
Blackport, R., and J. A. Screen, 2021: Observed Statistical Connections Overestimate the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate. Journal of Climate, 34, 3021–3038, https://doi.org/10.1175/JCLI-D-20-0293.1.
Hopsch, S., J. Cohen, and K. Dethloff, 2012: Analysis of a link between fall Arctic sea ice concentration and atmospheric patterns in the following winter. Tellus A: Dynamic Meteorology and Oceanography, 64, 18624, https://doi.org/10.3402/tellusa.v64i0.18624.
Hoskins, B., and T. Woollings, 2015: Persistent Extratropical Regimes and Climate Extremes. Curr Clim Change Rep, 1, 115–124, https://doi.org/10.1007/s40641-015-0020-8.
Kolstad, E. W., and J. A. Screen, 2019: Nonstationary Relationship Between Autumn Arctic Sea Ice and the Winter North Atlantic Oscillation. Geophys. Res. Lett., 46, 7583–7591, https://doi.org/10.1029/2019GL083059.
Liu, J., J. A. Curry, H. Wang, M. Song, and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall. Proc. Nat. Acad. Sci., 109, 4074–4079.
Overland, J., J. A. Francis, R. Hall, E. Hanna, S.-J. Kim, and T. Vihma, 2015: The Melting Arctic and Midlatitude Weather Patterns: Are They Connected? Journal of Climate, 28, 7917–7932, https://doi.org/10.1175/JCLI-D-14-00822.1.
Peings, Y., 2019: Ural Blocking as a Driver of Early-Winter Stratospheric Warmings. Geophys. Res. Lett., 46, 5460–5468, https://doi.org/10.1029/2019GL082097.
Ruggieri, P., R. Buizza, and G. Visconti, 2016: On the link between Barents-Kara sea ice variability and European blocking. Journal of Geophysical Research: Atmospheres, 121, 5664–5679, https://doi.org/10.1002/2015JD024021.
Siew, P. Y. F., C. Li, M. Ting, S. P. Sobolowski, Y. Wu, and X. Chen, 2021: North Atlantic Oscillation in winter is largely insensitive to autumn Barents-Kara sea ice variability. Science Advances, 7, eabg4893, https://doi.org/10.1126/sciadv.abg4893.
Tang, Q., X. Zhang, X. Yang, and J. A. Francis, 2013: Cold winter extremes in northern continents linked to Arctic sea ice loss. Environ. Res. Lett., 8, 014036, https://doi.org/10.1088/1748-9326/8/1/014036.
Wilks, D. S., 2016: “The Stippling Shows Statistically Significant Grid Points”: How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It. Bulletin of the American Meteorological Society, 97, 2263–2273, https://doi.org/10.1175/BAMS-D-15-00267.1.
Yang, X.-Y., X. Yuan, and M. Ting, 2016: Dynamical Link between the Barents–Kara Sea Ice and the Arctic Oscillation. Journal of Climate, 29, 5103–5122, https://doi.org/10.1175/JCLI-D-15-0669.1.
Citation: https://doi.org/10.5194/egusphere-2023-1646-RC2 -
EC1: 'Comment on egusphere-2023-1646', Lukas Papritz, 13 Sep 2023
Dear Authors
Thank you for submitting your manuscript to WCD. The two reviewers have carefully evaluated your manuscript. Unfortunately, as you can see from their comments, they have fundamental concerns with the main points of criticism being (i) that the study does not convey sufficient new results that go beyond the existing literature and (ii) there are major methodological problems (model - observation comparison, small sample size and lack of control of false-discovery-rate, causation from correlation).
Addressing these points needs substantial changes to the manuscript, which go beyond major revisions, requiring ample time and likely resulting in an essentially new paper. For this reason, I recommend to withdraw the paper at the present stage and re-evaluate it. If you choose this option, I would like to encourage you to nevertheless address the main points of criticism in a publicly available final author comment.
Please don't hesitate to contact me if you have any questions or need further information.
Best regards,
Lukas PapritzCitation: https://doi.org/10.5194/egusphere-2023-1646-EC1 -
AC1: 'Reply on EC1', Di Cai, 15 Sep 2023
Dear Dr. Lukas Papritz,
Thank you for your detailed feedback and the time taken by the reviewers to evaluate our manuscript. We appreciate the constructive comments and understand the concerns raised by the reviewers.
We are currently in the process of making revisions to the manuscript based on the comments received. Once we've made the necessary changes and improvements, we'll provide a detailed response to each comment.
Thank you for your understanding and patience. We will reach out once we are ready to share the revised manuscript and our detailed responses to the comments.
Best wishes,
Di Cai
Citation: https://doi.org/10.5194/egusphere-2023-1646-AC1
-
AC1: 'Reply on EC1', Di Cai, 15 Sep 2023
Status: closed
-
RC1: 'Comment on egusphere-2023-1646', Anonymous Referee #1, 28 Aug 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1646/egusphere-2023-1646-RC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-1646', Anonymous Referee #2, 01 Sep 2023
This study examines the links between autumn sea ice in the Barents-Kara sea ice and European winter cold extremes. The authors find low sea ice is associated with a weakened stratospheric polar vortex, a negative NAO/AO, more frequent blocking, and more frequent cold extremes over Europe. The authors conclude from this that sea ice retreat is an important driver of winter weather extremes. The authors also perform an evaluation of the sea ice variability and sea ice-circulation links in climate models, and find they perform very poorly.
Overall, there are many fundamental issues with the analysis and interpretation. This includes assuming causation from correlation, sampling issues, and inappropriate model-observation comparisons. Even if some of these may be able to be addressed with major revisions (e.g. toning down conclusions and additional analysis), it is not clear to me what the novelty of the study is. Because of these reasons, I recommend this paper be rejected.
Note that while my comments are very similar to reviewer#1’s comments, I wrote this review before looking at their comments.
Major issues:
1. The authors assume the atmospheric circulation and temperature anomalies that are linked with reduced sea ice are caused by the reduced sea ice. There are strong statements about causality throughout the paper, even explicitly stating that the sea ice anomalies are causing the subsequent circulation anomalies. However, correlation does not necessarily imply causation. Indeed, there have been many studies arguing that these correlations are not caused by sea ice loss, but rather both are driven by the same circulation patterns. This is the case even when investigating the lagged connection from autumn sea ice to the winter circulation/temperatures, as is examined here (e.g. Peings 2019; Blackport and Screen 2021). Strong statements about the causality need to be removed and the issues with causality need to be discussed.
2. The analysis is based on very small sample sizes, and many of the results presented are not, or barely statistically significant. These weak and non-robust connections seen in the figures are often described in detail and with a lot of authority in the text as if are they very robust. In addition, it does not appear that the false discovery rate was controlled for in the maps (Wilks 2016), which would even further reduce the significance. Furthermore, it also has been shown that the relationship between autumn Barents-kara sea ice and the NAO is not robust and nonstationary over time, with it displaying opposite signed relationships in the recent past (Kolstad and Screen 2019). This further questions the robustness of the results presented here. For this paper to be publishable, the false discovery rate needs to be controlled for, and the authors would need to substantially revise the text to put less focus on links that are not statistically significant.
3. The model-observation comparisons are not appropriate and demonstrate a fundamental misunderstanding of the analysis and/or the data. The year-to-year variability in observations and in individual model runs is almost entirely due to internal variability. However, the phases of internal variability will not occur at the same time in each model realization (and in observations), so averaging over all model realizations will average out the internal variability. So of course the year-to-year variability in the model is low compared to observations, because you have removed the variability by averaging across the different runs! This flawed analysis leads the authors to make very strong statements about the capability of the models that are not supported.
To do the analysis correctly, you need to compare the observations to the spread of results in individual runs, not the ensemble mean. This is the case for both the analysis of the sea ice variability and the composites of the circulation over low and high sea ice. Note that you are probably going to want to use a lot more than 13 simulations for a proper comparison. The cross-ensemble spread will likely be very large due to internal variability, even within the same model (see e.g. Siew et al. 2021; Blackport and Screen 2021)
4. The novelty of the study is unclear. This study identifies the statistical connections between reduced sea ice in the Barents-Kara sea and the winter circulation and cold extremes. However, these links are all very well established and have been for a while now (e.g. Hopsch et al. 2012; Liu et al. 2012; Tang et al. 2013; Overland et al. 2015; Yang et al. 2016; Ruggieri et al. 2016; Blackport and Screen 2021) . There are still a lot of outstanding questions around this topic (e.g. the causality and the robustness of these connections), but this study does not address any of these. I don’t see any new insight that this study brings to the existing literature.
Other comments:
L13-15: I don’t really agree with this statement, at least for cold extremes, which this paper is about. It is well established that there are statistical correlations between the Arctic and midlatitude cold extremes. Where there is no consensus on is whether these statistical connections are a causal response to sea ice, whether they are relevant for climate change, plus many other questions.
L15-16: This statement is at best misleading about the results presented. I typically associate “decline in sea ice” with the long-term trend of disappearing sea ice, not year-to-year variability. This study uses detrended data, so it is not about the decline of sea ice. The long-term decline in sea ice is in fact associated with a reduction in cold extremes over Europe.
L21-22: Similar to above, the word “retreat” implies a long-term trend which is not what the paper is about.
L23:Artic --> Arctic
L40-42: I don’t follow the logic here. Why does the fact that there is a connection in observations suggest that the latter sea ice forces the atmosphere? The main message of Blackport et al. 2019 (that this sentence seems to be disputing) is that the correlation do not appear to be driven by sea ice.
L46-56: The evidence and theoretical basis for the mechanisms described here linking sea ice loss to the midlatitude circulation are heavily disputed (e.g. Barnes 2013; Hoskins and Woollings 2015; Barnes and Screen 2015; Blackport and Screen 2020; Siew et al. 2021). Overall, this introduction is not a very accurate representation of the literature, and it does not accurately capture the outstanding questions in field.
L61-64: It is an exaggeration to say that the capability of the models to simulate these things is ‘limited’. Models have their biases, but when like-for-like comparisons are made, models tend to do quite well (e.g Blackport and Screen 2021).
L80: Why these 13 models? There is a lot more model data than this that is publicly available. I would recommend using as much model data as possible because of the large amount of internal variability.
L112: I assume this should be below -0.8 standard deviations for the low years.
L112-115: Are the results sensitive to the exact threshold used? With so few years, they might be.
L132: I don’t see a wave-like pattern in the Z100 results.
L183-195: I am not seeing what the authors are seeing in Fig 4. It seems to me that the authors are overinterpreting small month-to-month changes that are not statistically significant (see major comment 2).
L204: I think that the ‘Z500’ should be ‘Z100’?
L348-350: Even ignoring the issues with the model-observation comparisons, how would this provide an explanation for the ‘suboptimal climate sensitivity assessments’? What suboptimal climate sensitivity assessments is this referring to?
References:
Barnes, E. A., 2013: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophys. Res. Lett., 40, 4734–4739, https://doi.org/10.1002/grl.50880.
Barnes, E. A., and J. A. Screen, 2015: The impact of Arctic warming on the midlatitude jet-stream: Can it? Has it? Will it? WIREs Clim. Change, 6, 277–286, https://doi.org/10.1002/wcc.337.
Blackport, R., and J. A. Screen, 2020: Weakened evidence for mid-latitude impacts of Arctic warming. Nature Climate Change, 10, 1065–1066, https://doi.org/10.1038/s41558-020-00954-y.
Blackport, R., and J. A. Screen, 2021: Observed Statistical Connections Overestimate the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate. Journal of Climate, 34, 3021–3038, https://doi.org/10.1175/JCLI-D-20-0293.1.
Hopsch, S., J. Cohen, and K. Dethloff, 2012: Analysis of a link between fall Arctic sea ice concentration and atmospheric patterns in the following winter. Tellus A: Dynamic Meteorology and Oceanography, 64, 18624, https://doi.org/10.3402/tellusa.v64i0.18624.
Hoskins, B., and T. Woollings, 2015: Persistent Extratropical Regimes and Climate Extremes. Curr Clim Change Rep, 1, 115–124, https://doi.org/10.1007/s40641-015-0020-8.
Kolstad, E. W., and J. A. Screen, 2019: Nonstationary Relationship Between Autumn Arctic Sea Ice and the Winter North Atlantic Oscillation. Geophys. Res. Lett., 46, 7583–7591, https://doi.org/10.1029/2019GL083059.
Liu, J., J. A. Curry, H. Wang, M. Song, and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall. Proc. Nat. Acad. Sci., 109, 4074–4079.
Overland, J., J. A. Francis, R. Hall, E. Hanna, S.-J. Kim, and T. Vihma, 2015: The Melting Arctic and Midlatitude Weather Patterns: Are They Connected? Journal of Climate, 28, 7917–7932, https://doi.org/10.1175/JCLI-D-14-00822.1.
Peings, Y., 2019: Ural Blocking as a Driver of Early-Winter Stratospheric Warmings. Geophys. Res. Lett., 46, 5460–5468, https://doi.org/10.1029/2019GL082097.
Ruggieri, P., R. Buizza, and G. Visconti, 2016: On the link between Barents-Kara sea ice variability and European blocking. Journal of Geophysical Research: Atmospheres, 121, 5664–5679, https://doi.org/10.1002/2015JD024021.
Siew, P. Y. F., C. Li, M. Ting, S. P. Sobolowski, Y. Wu, and X. Chen, 2021: North Atlantic Oscillation in winter is largely insensitive to autumn Barents-Kara sea ice variability. Science Advances, 7, eabg4893, https://doi.org/10.1126/sciadv.abg4893.
Tang, Q., X. Zhang, X. Yang, and J. A. Francis, 2013: Cold winter extremes in northern continents linked to Arctic sea ice loss. Environ. Res. Lett., 8, 014036, https://doi.org/10.1088/1748-9326/8/1/014036.
Wilks, D. S., 2016: “The Stippling Shows Statistically Significant Grid Points”: How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It. Bulletin of the American Meteorological Society, 97, 2263–2273, https://doi.org/10.1175/BAMS-D-15-00267.1.
Yang, X.-Y., X. Yuan, and M. Ting, 2016: Dynamical Link between the Barents–Kara Sea Ice and the Arctic Oscillation. Journal of Climate, 29, 5103–5122, https://doi.org/10.1175/JCLI-D-15-0669.1.
Citation: https://doi.org/10.5194/egusphere-2023-1646-RC2 -
EC1: 'Comment on egusphere-2023-1646', Lukas Papritz, 13 Sep 2023
Dear Authors
Thank you for submitting your manuscript to WCD. The two reviewers have carefully evaluated your manuscript. Unfortunately, as you can see from their comments, they have fundamental concerns with the main points of criticism being (i) that the study does not convey sufficient new results that go beyond the existing literature and (ii) there are major methodological problems (model - observation comparison, small sample size and lack of control of false-discovery-rate, causation from correlation).
Addressing these points needs substantial changes to the manuscript, which go beyond major revisions, requiring ample time and likely resulting in an essentially new paper. For this reason, I recommend to withdraw the paper at the present stage and re-evaluate it. If you choose this option, I would like to encourage you to nevertheless address the main points of criticism in a publicly available final author comment.
Please don't hesitate to contact me if you have any questions or need further information.
Best regards,
Lukas PapritzCitation: https://doi.org/10.5194/egusphere-2023-1646-EC1 -
AC1: 'Reply on EC1', Di Cai, 15 Sep 2023
Dear Dr. Lukas Papritz,
Thank you for your detailed feedback and the time taken by the reviewers to evaluate our manuscript. We appreciate the constructive comments and understand the concerns raised by the reviewers.
We are currently in the process of making revisions to the manuscript based on the comments received. Once we've made the necessary changes and improvements, we'll provide a detailed response to each comment.
Thank you for your understanding and patience. We will reach out once we are ready to share the revised manuscript and our detailed responses to the comments.
Best wishes,
Di Cai
Citation: https://doi.org/10.5194/egusphere-2023-1646-AC1
-
AC1: 'Reply on EC1', Di Cai, 15 Sep 2023
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